Oreilly Live Training Agents

O'Reilly Live Training - Getting Started with LLM Agents using LangChain & LangGraph

Quick Setup (Recommended: uv)

The fastest way to get started is using [uv](https://github.com/astral-sh/uv), a modern Python package manager:

1. **Install uv:**

   curl -LsSf https://astral.sh/uv/install.sh | sh

2. **Create and activate virtual environment:**

   uv venv .venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. **Install dependencies:**

   uv pip install -r requirements/requirements.txt

4. **Set up your environment variables:**

   cp .env.example .env
   # Edit .env and add your API keys

5. **Install Jupyter kernel for this project:**

   python -m ipykernel install --user --name=oreilly-agents --display-name "O'Reilly Agents (oreilly-agents)"

Alternative Setup Methods

Using Conda

• Install anaconda
• Create an environment: conda create -n oreilly-agents python=3.11
• Activate your environment with: conda activate oreilly-agents
• Install requirements with: pip install -r requirements/requirements.txt
• Setup your openai API key

Using Pip

1. **Create a Virtual Environment:** Navigate to your project directory. If using Python 3's built-in `venv`: `python -m venv oreilly-agents` If you're using `virtualenv`: `virtualenv oreilly-agents`

2. **Activate the Virtual Environment:**

   • On Windows: .\oreilly-agents\Scripts\activate
   • On macOS and Linux: source oreilly-agents/bin/activate

3. **Install Dependencies from `requirements.txt`:**

   pip install -r ./requirements/requirements.txt

Remember to deactivate the virtual environment afterwards: `deactivate`

Setup your .env file

Copy the `.env.example` file to `.env` and add your API keys:

cp .env.example .env

Then edit `.env` and add your keys: